Paper Citation Record · LEDGER

Continual Learning on Graphs: Challenges, Solutions, and Opportunities

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2402.11565.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2402.11565 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T15:53:23.758308Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

5
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 3e5bc351-5a11-4dab-bfa2-ac9318662173 · inbound

Prompt-Driven Continual Graph Learning cites this paper.

Prompt-Driven Continual Graph Learning Continual Learning on Graphs: Challenges, Solutions, and Opportunities

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-08T15:53:23.758308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e264785-0ffa-4017-97c7-9a087ec988f3 · inbound

Learning without Isolation: Pathway Protection for Continual Learning cites this paper.

Learning without Isolation: Pathway Protection for Continual Learning Continual Learning on Graphs: Challenges, Solutions, and Opportunities

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T14:33:13.801867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b06f51dd-97d8-4120-be10-fda0c3aa7974 · inbound

ETT-CKGE: Efficient Task-driven Tokens for Continual Knowledge Graph Embedding cites this paper.

ETT-CKGE: Efficient Task-driven Tokens for Continual Knowledge Graph Embedding Continual Learning on Graphs: Challenges, Solutions, and Opportunities

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T05:24:25.348415Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 60a0b3bd-91fe-4f67-8459-7bb77e9006af · inbound

Empowering Power Outage Prediction with Spatially Aware Hybrid Graph Neural Networks and Contrastive Learning cites this paper.

Empowering Power Outage Prediction with Spatially Aware Hybrid Graph Neural Networks and Contrastive Learning Continual Learning on Graphs: Challenges, Solutions, and Opportunities

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-10T22:45:51.002022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 991f9afe-2c05-4d77-bfe4-d216510594e5 · inbound

UFO: A Unified Flow-Oriented Framework for Robust Continual Graph Learning cites this paper.

UFO: A Unified Flow-Oriented Framework for Robust Continual Graph Learning Continual Learning on Graphs: Challenges, Solutions, and Opportunities

Reference 14

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T05:31:25.375156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 40694291-77b6-4b93-bd25-9591cfda7dc2 · inbound

DRIFT: A Benchmark for Task-Free Continual Graph Learning with Continuous Distribution Shifts cites this paper.

DRIFT: A Benchmark for Task-Free Continual Graph Learning with Continuous Distribution Shifts Continual Learning on Graphs: Challenges, Solutions, and Opportunities

Reference 32

Resolution: metadata mismatch; arxiv_id, observed 2026-05-14T19:42:53.558273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a331a929-eb5c-48ca-ba33-e9b5f94d50c9 · inbound

DRIFT: A Benchmark for Task-Free Continual Graph Learning with Continuous Distribution Shifts cites this paper.

DRIFT: A Benchmark for Task-Free Continual Graph Learning with Continuous Distribution Shifts Continual Learning on Graphs: Challenges, Solutions, and Opportunities

Reference 32

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T05:49:48.081656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6aa1335d-16fa-4fae-b054-9a31803ac533 · inbound

DRIFT: A Benchmark for Task-Free Continual Graph Learning with Continuous Distribution Shifts cites this paper.

DRIFT: A Benchmark for Task-Free Continual Graph Learning with Continuous Distribution Shifts Continual Learning on Graphs: Challenges, Solutions, and Opportunities

Reference 32

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T21:55:06.070586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 08de0b16-3cc7-459a-afc1-701b31119f92 · inbound

Towards Foundation Models for Relational Databases with Language Models and Graph Neural Networks cites this paper.

Towards Foundation Models for Relational Databases with Language Models and Graph Neural Networks Continual Learning on Graphs: Challenges, Solutions, and Opportunities

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-19T18:42:43.749868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f546e3af-e3c8-4494-8ed2-285db20a9e26 · inbound

G2LoRA: Gradient Orthogonal Low-Rank Adaptation Framework for Graph Continual Learning on Text-Attributed Graphs cites this paper.

G2LoRA: Gradient Orthogonal Low-Rank Adaptation Framework for Graph Continual Learning on Text-Attributed Graphs Continual Learning on Graphs: Challenges, Solutions, and Opportunities

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-07-01T22:26:17.539001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.